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Realization and identification algorithm for stochastic LPV state-space models with exogenous inputs ?

机译:具有外部输入的随机LPV状态空间模型的实现和识别算法

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In this paper, we present a realization and an identification algorithm for stochasticLinear Parameter-Varying State-Space Affine(LPV-SSA) representations. The proposed realization algorithm combines the deterministic LPV input output to LPV state-space realization scheme based on correlation analysis with a stochastic covariance realization algorithm. Based on this realization algorithm, a computationally efficient and statistically consistent identification algorithm is proposed to estimate the LPV model matrices, which are computed from the empirical covariance matrices of outputs, inputs and scheduling signal observations. The effectiveness of the proposed algorithm is shown via a numerical case study.
机译:在本文中,我们提出了一种随机线性参数变化状态空间仿射(LPV-SSA)表示的实现和一种识别算法。提出的实现算法将确定性的LPV输入输出与基于相关性分析的LPV状态空间实现方案结合了随机协方差实现算法。基于该实现算法,提出了一种计算效率高且统计一致性的识别算法,用于估计LPV模型矩阵,该矩阵是根据输出,输入和调度信号观测值的经验协方差矩阵计算得出的。数值算例表明了该算法的有效性。

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